877 resultados para High-performance computing hyperspectral imaging
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This dissertation investigates high performance cooperative localization in wireless environments based on multi-node time-of-arrival (TOA) and direction-of-arrival (DOA) estimations in line-of-sight (LOS) and non-LOS (NLOS) scenarios. Here, two categories of nodes are assumed: base nodes (BNs) and target nodes (TNs). BNs are equipped with antenna arrays and capable of estimating TOA (range) and DOA (angle). TNs are equipped with Omni-directional antennas and communicate with BNs to allow BNs to localize TNs; thus, the proposed localization is maintained by BNs and TNs cooperation. First, a LOS localization method is proposed, which is based on semi-distributed multi-node TOA-DOA fusion. The proposed technique is applicable to mobile ad-hoc networks (MANETs). We assume LOS is available between BNs and TNs. One BN is selected as the reference BN, and other nodes are localized in the coordinates of the reference BN. Each BN can localize TNs located in its coverage area independently. In addition, a TN might be localized by multiple BNs. High performance localization is attainable via multi-node TOA-DOA fusion. The complexity of the semi-distributed multi-node TOA-DOA fusion is low because the total computational load is distributed across all BNs. To evaluate the localization accuracy of the proposed method, we compare the proposed method with global positioning system (GPS) aided TOA (DOA) fusion, which are applicable to MANETs. The comparison criterion is the localization circular error probability (CEP). The results confirm that the proposed method is suitable for moderate scale MANETs, while GPS-aided TOA fusion is suitable for large scale MANETs. Usually, TOA and DOA of TNs are periodically estimated by BNs. Thus, Kalman filter (KF) is integrated with multi-node TOA-DOA fusion to further improve its performance. The integration of KF and multi-node TOA-DOA fusion is compared with extended-KF (EKF) when it is applied to multiple TOA-DOA estimations made by multiple BNs. The comparison depicts that it is stable (no divergence takes place) and its accuracy is slightly lower than that of the EKF, if the EKF converges. However, the EKF may diverge while the integration of KF and multi-node TOA-DOA fusion does not; thus, the reliability of the proposed method is higher. In addition, the computational complexity of the integration of KF and multi-node TOA-DOA fusion is much lower than that of EKF. In wireless environments, LOS might be obstructed. This degrades the localization reliability. Antenna arrays installed at each BN is incorporated to allow each BN to identify NLOS scenarios independently. Here, a single BN measures the phase difference across two antenna elements using a synchronized bi-receiver system, and maps it into wireless channel’s K-factor. The larger K is, the more likely the channel would be a LOS one. Next, the K-factor is incorporated to identify NLOS scenarios. The performance of this system is characterized in terms of probability of LOS and NLOS identification. The latency of the method is small. Finally, a multi-node NLOS identification and localization method is proposed to improve localization reliability. In this case, multiple BNs engage in the process of NLOS identification, shared reflectors determination and localization, and NLOS TN localization. In NLOS scenarios, when there are three or more shared reflectors, those reflectors are localized via DOA fusion, and then a TN is localized via TOA fusion based on the localization of shared reflectors.
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Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.
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PURPOSE Abundant expression of somatostatin receptors (sst) is a characteristic of neuroendocrine tumors (NET). Thus, radiolabeled somatostatin analogs have emerged as important tools for both in vivo diagnosis and therapy of NET. The two compounds most often used in functional imaging with positron emission tomography (PET) are (68)Ga-DOTATATE and (68)Ga-DOTATOC. Both analogs share a quite similar sst binding profile. However, the in vitro affinity of (68)Ga-DOTATATE in binding the sst subtype 2 (sst2) is approximately tenfold higher than that of (68)Ga-DOTATOC. This difference may affect their efficiency in detection of NET lesions, as sst2 is the predominant receptor subtype on gastroenteropancreatic NET. We thus compared the diagnostic value of PET/CT with both radiolabeled somatostatin analogs ((68)Ga-DOTATATE and (68)Ga-DOTATOC) in the same patients with gastroenteropancreatic NET. PATIENTS AND METHODS Twenty-seven patients with metastatic gastroenteropancreatic NET underwent (68)Ga-DOTATOC and (68)Ga-DOTATATE PET/CT as part of the workup before prospective peptide receptor radionuclide therapy (PRRT). The performance of both imaging methods was analyzed and compared for detection of individual lesions per patient and for eight defined body regions. A region was regarded as positive if at least one lesion was detected in that region. In addition, radiopeptide uptake in terms of the maximal standardized uptake value (SUV(max)) was compared for concordant lesions and renal parenchyma. RESULTS Fifty-one regions were found positive with both (68)Ga-DOTATATE and (68)Ga-DOTATOC. Overall, however, significantly fewer lesions were detected with (68)Ga-DOTATATE in comparison with (68)Ga-DOTATOC (174 versus 179, p < 0.05). Mean (68)Ga-DOTATATE SUV(max) across all lesions was significantly lower compared with (68)Ga-DOTATOC (16.9 ± 6.8 versus 22.1 ± 12.0, p < 0.01). Mean SUV(max) for renal parenchyma was not significantly different between (68)Ga-DOTATATE and (68)Ga-DOTATOC (12.6 ± 2.6 versus 12.6 ± 2.7). CONCLUSIONS (68)Ga-DOTATOC and (68)Ga-DOTATATE possess similar diagnostic accuracy for detection of gastroenteropancreatic NET lesions (with a potential advantage of (68)Ga-DOTATOC) despite their evident difference in affinity for sst2. Quite unexpectedly, maximal uptake of (68)Ga-DOTATOC tended to be higher than its (68)Ga-DOTATATE counterpart. However, tumor uptake shows high inter- and intraindividual variance with unpredictable preference of one radiopeptide. Thus, our data encourage the application of different sst ligands to enable personalized imaging and therapy of gastroenteropancreatic NET with optimal targeting of tumor receptors.
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Preclinical studies using animal models have shown that grey matter plasticity in both perilesional and distant neural networks contributes to behavioural recovery of sensorimotor functions after ischaemic cortical stroke. Whether such morphological changes can be detected after human cortical stroke is not yet known, but this would be essential to better understand post-stroke brain architecture and its impact on recovery. Using serial behavioural and high-resolution magnetic resonance imaging (MRI) measurements, we tracked recovery of dexterous hand function in 28 patients with ischaemic stroke involving the primary sensorimotor cortices. We were able to classify three recovery subgroups (fast, slow, and poor) using response feature analysis of individual recovery curves. To detect areas with significant longitudinal grey matter volume (GMV) change, we performed tensor-based morphometry of MRI data acquired in the subacute phase, i.e. after the stage compromised by acute oedema and inflammation. We found significant GMV expansion in the perilesional premotor cortex, ipsilesional mediodorsal thalamus, and caudate nucleus, and GMV contraction in the contralesional cerebellum. According to an interaction model, patients with fast recovery had more perilesional than subcortical expansion, whereas the contrary was true for patients with impaired recovery. Also, there were significant voxel-wise correlations between motor performance and ipsilesional GMV contraction in the posterior parietal lobes and expansion in dorsolateral prefrontal cortex. In sum, perilesional GMV expansion is associated with successful recovery after cortical stroke, possibly reflecting the restructuring of local cortical networks. Distant changes within the prefrontal-striato-thalamic network are related to impaired recovery, probably indicating higher demands on cognitive control of motor behaviour.
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To date, despite a large body of evidence in favor of the advantage of an effect-related focus of attention compared with a movement-related focus of attention in motor control and learning, the role of vision in this context remains unclear. Therefore, in a golf-putting study, the relation between attentional focus and gaze behavior (in particular, quiet eye, or QE) was investigated. First, the advantage of an effect-related focus, as well as of a long QE duration, could be replicated. Furthermore, in the online-demanding task of golf putting, high performance was associated with later QE offsets. Most decisively, an interaction between attentional focus and gaze behavior was revealed in such a way that the efficiency of the QE selectively manifested under movement-related focus instructions. As these findings suggest neither additive effects nor a causal chain, an alternative hypothesis is introduced explaining positive QE effects by the inhibition of not-to-be parameterized movement variants.
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Recent geomorphological observations as well as chemical and thermodynamic studies demonstrate that liquid water should be stable today on the Martian surface at some times of the day. In Martian conditions, brines would be particularly more stable than pure water because salts can depress the freezing point and lower the evaporation rate of water. Despite this evidence, no clear spectral signature of liquid has been observed so far by the hyperspectral imaging spectrometers OMEGA and CRISM. However, past spectral analysis lacks a good characterization of brines׳ spectral signatures. This study thus aims to determine how liquid brines can be detected on Mars by spectroscopy. In this way, laboratory experiments were performed for reproducing hydration and dehydration cycles of various brines while measuring their spectral signatures. The resulting spectra first reveal a very similar spectral evolution for the various brine types and pure water, with the main difference observed at the end of the dehydration with the crystallization of various hydrated minerals from brines. The main characteristic of this spectral behavior is an important decoupling between the evolution of albedo and hydration bands depths. During most of the wetting/drying processes, spectra usually display a low albedo associated with shallow water absorption band depths. Strong water absorption band depth and high albedo are respectively only observed when the surface is very wet and when the surface is very dry. These experiments can thus explain why the currently active Martian features attributed to the action of a liquid are only associated with low albedo and very weak spectral signatures. Hydration experiments also reveal that deliquescence occurs easily even at low temperature and moderate soil water vapor pressure and could thus cause seasonal darkening on Mars. These experiments demonstrate that the absence of water absorptions in CRISM in the middle afternoon does not rule out water activity and suggest future spectral investigations to identify water on the Martian surface.
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OBJECTIVE The aim of this study was to compare quantitative and semiquantitative parameters (signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], image quality, diagnostic confidence) from a standard brain magnetic resonance imaging examination encompassing common neurological disorders such as demyelinating disease, gliomas, cerebrovascular disease, and epilepsy, with comparable sequence protocols and acquisition times at 3 T and at 7 T. MATERIALS AND METHODS Ten healthy volunteers and 4 subgroups of 40 patients in total underwent comparable magnetic resonance protocols with standard diffusion-weighted imaging, 2D and 3D turbo spin echo, 2D and 3D gradient echo and susceptibility-weighted imaging of the brain (10 sequences) at 3 T and 7 T. The subgroups comprised patients with either lesional (n = 5) or nonlesional (n = 4) epilepsy, intracerebral tumors (n = 11), demyelinating disease (n = 11) (relapsing-remitting multiple sclerosis [MS, n = 9], secondary progressive MS [n = 1], demyelinating disease not further specified [n = 1]), or chronic cerebrovascular disorders [n = 9]). For quantitative analysis, SNR and CNR were determined. For a semiquantitative assessment of the diagnostic confidence, a 10-point scale diagnostic confidence score (DCS) was applied. Two experienced radiologists with additional qualification in neuroradiology independently assessed, blinded to the field strength, 3 pathology-specific imaging criteria in each of the 4 disease groups and rated their diagnostic confidence. The overall image quality was semiquantitatively assessed using a 4-point scale taking into account whether diagnostic decision making was hampered by artifacts or not. RESULTS Without correction for spatial resolution, SNR was higher at 3 T except in the T2 SPACE 3D, DWI single shot, and DIR SPACE 3D sequences. The SNR corrected by the ratio of 3 T/7 T voxel sizes was higher at 7 T than at 3 T in 10 of 11 sequences (all except for T1 MP2RAGE 3D).In CNR, there was a wide variation between sequences and patient cohorts, but average CNR values were broadly similar at 3 T and 7 T.DCS values for all 4 pathologic entities were higher at 7 T than at 3 T. The DCS was significantly higher at 7 T for diagnosis and exclusion of cortical lesions in vascular disease. A tendency to higher DCS at 7 T for cortical lesions in MS was observed, and for the depiction of a central vein and iron deposits within MS lesions. Despite motion artifacts, DCS values were higher at 7 T for the diagnosis and exclusion of hippocampal sclerosis in mesial temporal lobe epilepsy (improved detection of the hippocampal subunits). Interrater agreement was 69.7% at 3 T and 93.3% at 7 T. There was no significant difference in the overall image quality score between 3 T and 7 T taking into account whether diagnostic decision making was hampered by artifacts or not. CONCLUSIONS Ultra-high-field magnetic resonance imaging at 7 T compared with 3 T yielded an improved diagnostic confidence in the most frequently encountered neurologic disorders. Higher spatial resolution and contrast were identified as the main contributory factors.
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High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.
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The oceans play a critical role in the Earth's climate, but unfortunately, the extent of this role is only partially understood. One major obstacle is the difficulty associated with making high-quality, globally distributed observations, a feat that is nearly impossible using only ships and other ocean-based platforms. The data collected by satellite-borne ocean color instruments, however, provide environmental scientists a synoptic look at the productivity and variability of the Earth's oceans and atmosphere, respectively, on high-resolution temporal and spatial scales. Three such instruments, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard ORBIMAGE's OrbView-2 satellite, and two Moderate Resolution Imaging Spectroradiometers (MODIS) onboard the National Aeronautic and Space Administration's (NASA) Terra and Aqua satellites, have been in continuous operation since September 1997, February 2000, and June 2002, respectively. To facilitate the assembly of a suitably accurate data set for climate research, members of the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project and SeaWiFS Project Offices devote significant attention to the calibration and validation of these and other ocean color instruments. This article briefly presents results from the SIMBIOS and SeaWiFS Project Office's (SSPO) satellite ocean color validation activities and describes the SeaWiFS Bio-optical Archive and Storage System (SeaBASS), a state-of-the-art system for archiving, cataloging, and distributing the in situ data used in these activities.
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The outer western Crimean shelf of the Black Sea is a natural laboratory to investigate effects of stable oxic versus varying hypoxic conditions on seafloor biogeochemical processes and benthic community structure. Bottom-water oxygen concentrations ranged from normoxic (175 µmol O2/L) and hypoxic (< 63 µmol O2/L) or even anoxic/sulfidic conditions within a few kilometers' distance. Variations in oxygen concentrations between 160 and 10 µmol/L even occurred within hours close to the chemocline at 134 m water depth. Total oxygen uptake, including diffusive as well as fauna-mediated oxygen consumption, decreased from 15 mmol/m**2/d on average in the oxic zone, to 7 mmol/m**2/d on average in the hypoxic zone, correlating with changes in macrobenthos composition. Benthic diffusive oxygen uptake rates, comprising respiration of microorganisms and small meiofauna, were similar in oxic and hypoxic zones (on average 4.5 mmol/m**2/d), but declined to 1.3 mmol/m**2/d in bottom waters with oxygen concentrations below 20 µmol/L. Measurements and modeling of porewater profiles indicated that reoxidation of reduced compounds played only a minor role in diffusive oxygen uptake under the different oxygen conditions, leaving the major fraction to aerobic degradation of organic carbon. Remineralization efficiency decreased from nearly 100 % in the oxic zone, to 50 % in the oxic-hypoxic zone, to 10 % in the hypoxic-anoxic zone. Overall, the faunal remineralization rate was more important, but also more influenced by fluctuating oxygen concentrations, than microbial and geochemical oxidation processes.
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We used hyperspectral imaging to study short-term effects of bioturbation by lugworms (Arenicola marina) on the surficial biomass of microphytobenthos (MPB) in permeable marine sediments. Within days to weeks after the addition of a lugworm to a homogenized and recomposed sediment, the average surficial MPB biomass and its spatial heterogeneity were, respectively, 150 - 250% and 280% higher than in sediments without lugworms. The surficial sediment area impacted by a single medium-sized lugworm (~4 g wet weight) over this time-scale was at least 340 cm**2. While sediment reworking was the primary cause of the increased spatial heterogeneity, experiments with lugworm-mimics together with modeling showed that bioadvective porewater transport from depth to the sediment surface, as induced by the lugworm ventilating its burrow, was the main cause of the increased surficial MPB biomass. Although direct measurements of nutrient fluxes are lacking, our present data show that enhanced advective supply of nutrients from deeper sediment layers induced by faunal ventilation is an important mechanism that fuels high primary productivity at the surface of permeable sediments even though these systems are generally characterized by low standing stocks of nutrients and organic material.
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The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.
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This paper examines factors that encourage firms to go into supply chain collaborations (SCC) and relationships between SCC and supply chain performances (SCP), using a questionnaire survey on Thai automotive and electronics industries in 2012. OLS regression results show firms established supplier evaluation and audit system, system of rewards for high-performance supplier and long-term transactions with their supply chain partners under a competitive pressure are more closely cooperate with these partners on information sharing and decision synchronization. Instrumental variables regression indicates SCC arisen from competitive pressure, supplier evaluation and audit, a system of rewards for high-performance supplier and long-term relationship causally influence SCP such as on-time delivery, responsiveness to fast procurement, flexibility to customer need, and profit.